Model-based insulin sensitivity for early diagnosis of sepsis in critical care

OBJECTIVES To determine the diagnostic value of model-based insulin sensitivity (SI) as a new sepsis biomarker in critically ill patients, and compare its performance to classical inflammatory parameters. METHODS We monitored hourly SI levels in septic (n=19) and non-septic (n=19) critically ill...

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Main Authors:	Wan Shukeri, Wan Fadzlina, Md Ralib, Azrina, Jamaludin, Ummu Kulthum, Mat Nor, Mohd Basri
Format:	Conference or Workshop Item
Language:	English
Published:	2017
Subjects:	R Medicine (General)
Online Access:	http://irep.iium.edu.my/58199/ http://irep.iium.edu.my/58199/ http://irep.iium.edu.my/58199/3/5.%20ASMIC2017_ModelBasedInsulin.pdf

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recordtype	eprints
spelling	iium-581992017-08-29T06:31:04Z http://irep.iium.edu.my/58199/ Model-based insulin sensitivity for early diagnosis of sepsis in critical care Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri R Medicine (General) OBJECTIVES To determine the diagnostic value of model-based insulin sensitivity (SI) as a new sepsis biomarker in critically ill patients, and compare its performance to classical inflammatory parameters. METHODS We monitored hourly SI levels in septic (n=19) and non-septic (n=19) critically ill patients in a 24-hour follow-up study. Patients with type I or type II diabetes mellitus were excluded. SI levels were calculated by a validated glycemic control software, STAR TGC (Stochastic TARgeted Tight Glycemic Controller) (Christchurch, NZ). STAR TGC uses a physiological glucose-insulin system model coupled with stochastic models that capture SI variability in real time. RESULTS The median SI levels were lower in the sepsis group than in the non-sepsis group (1.9 x 10-4 L/mU/min vs 3.7 x 10-4 L/mU/min, P <0.0001). The areas under the receiver operating characteristic curve (AUROC) of the model-based SI for distinguishing non-sepsis from sepsis was 0.911, superior to white cells count (AUROC 0.611) and temperature (AUROC 0.618). The optimal cut-off value of the test was 2.9 x 10-4 L/mU/min. At this cut-off value, the sensitivity and specificity was 88.9% and 84.2%, respectively. The positive predictive value was 84.2%, while the negative predictive value was 88.9%. CONCLUSION The early and relevant decrease of SI in sepsis suggests that it might be a promising novel biomarker of sepsis in critical care. Low SI is diagnostic of sepsis, while high SI rules out sepsis, and these may be determined non-invasively in real time from glycemic control protocol data. 2017 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/58199/3/5.%20ASMIC2017_ModelBasedInsulin.pdf Wan Shukeri, Wan Fadzlina and Md Ralib, Azrina and Jamaludin, Ummu Kulthum and Mat Nor, Mohd Basri (2017) Model-based insulin sensitivity for early diagnosis of sepsis in critical care. In: Annual Scientific Meeting on Intensive Care (ASMIC 2017) : 1st Asian Pediatric Mechanical Ventilation Forum, 18th-20th August 2017, Kuala Lumpur. (Unpublished) http://msic.org.my/asmic2017/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	R Medicine (General)
spellingShingle	R Medicine (General) Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri Model-based insulin sensitivity for early diagnosis of sepsis in critical care
description	OBJECTIVES To determine the diagnostic value of model-based insulin sensitivity (SI) as a new sepsis biomarker in critically ill patients, and compare its performance to classical inflammatory parameters. METHODS We monitored hourly SI levels in septic (n=19) and non-septic (n=19) critically ill patients in a 24-hour follow-up study. Patients with type I or type II diabetes mellitus were excluded. SI levels were calculated by a validated glycemic control software, STAR TGC (Stochastic TARgeted Tight Glycemic Controller) (Christchurch, NZ). STAR TGC uses a physiological glucose-insulin system model coupled with stochastic models that capture SI variability in real time. RESULTS The median SI levels were lower in the sepsis group than in the non-sepsis group (1.9 x 10-4 L/mU/min vs 3.7 x 10-4 L/mU/min, P <0.0001). The areas under the receiver operating characteristic curve (AUROC) of the model-based SI for distinguishing non-sepsis from sepsis was 0.911, superior to white cells count (AUROC 0.611) and temperature (AUROC 0.618). The optimal cut-off value of the test was 2.9 x 10-4 L/mU/min. At this cut-off value, the sensitivity and specificity was 88.9% and 84.2%, respectively. The positive predictive value was 84.2%, while the negative predictive value was 88.9%. CONCLUSION The early and relevant decrease of SI in sepsis suggests that it might be a promising novel biomarker of sepsis in critical care. Low SI is diagnostic of sepsis, while high SI rules out sepsis, and these may be determined non-invasively in real time from glycemic control protocol data.
format	Conference or Workshop Item
author	Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri
author_facet	Wan Shukeri, Wan Fadzlina Md Ralib, Azrina Jamaludin, Ummu Kulthum Mat Nor, Mohd Basri
author_sort	Wan Shukeri, Wan Fadzlina
title	Model-based insulin sensitivity for early diagnosis of sepsis in critical care
title_short	Model-based insulin sensitivity for early diagnosis of sepsis in critical care
title_full	Model-based insulin sensitivity for early diagnosis of sepsis in critical care
title_fullStr	Model-based insulin sensitivity for early diagnosis of sepsis in critical care
title_full_unstemmed	Model-based insulin sensitivity for early diagnosis of sepsis in critical care
title_sort	model-based insulin sensitivity for early diagnosis of sepsis in critical care
publishDate	2017
url	http://irep.iium.edu.my/58199/ http://irep.iium.edu.my/58199/ http://irep.iium.edu.my/58199/3/5.%20ASMIC2017_ModelBasedInsulin.pdf
first_indexed	2023-09-18T21:22:17Z
last_indexed	2023-09-18T21:22:17Z
_version_	1777411961154174976

Model-based insulin sensitivity for early diagnosis of sepsis in critical care

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